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Above the Clouds: A Berkley View of Cloud Computing

Ambrust et al.RAD Lab (supported: google, amazon, microsoft, etc.)

CIS6000Paper Presentation: Mohammad Naeem

School of Computer Science (SOSC)University of Guelph

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gist of the paper

NO---Cloud Computing (CC) makes technical and economic sense there

May be some issues though

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focal points

o backgroundo advantageso reasons for later/potential successo becoming cloud computing provider: guidelineo moving to clouds: conditions foro utility computing: classeso cloud computing: economic ofo moving to cloud : economics ofo critical obstacles and opportunitieso recommendations

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outline

data center

= hardware+

system

software

application

software

(simple

software

installation

& m, control

over

versioning)

o utility computing (selling date center resources)

o SaaS --- software as a service

oThe data center’s hardware and software as a cloud

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advantages

o adding to the attractiveness of software service

o availability of an abundant amount of hardware

o under and over provisioning avoided

o quick results (1000 computers working on the same task simultaneously)

conditions for moving to cloudso demand varies with time (over-provisioning leads to under-utilization of resources)

o demand unknown in advance (a web start-up needing to support a sudden spike followed by a reduction in load)

o cost-associativity in case of batch-analytic (organizations that perform batch analytics can use the cost associativity of CC to finish the computation faster)

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types of utility computing

amazon web services

microsoft azure

google apple engine

Computation model

• X86 instruction set architecture

• CLR • pre-defined application structure & framework

storage model • block store to augmented key/blob store

• SQL data services • Mega-store/big table

networking model

• declarative specification of IP level topology

• programmer-defined application components

• fixed typology to accommodate 3-tier web app structure

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types of utility computing

google app engine

microsoft Azure

EC2

highest-level

lowest-level

possibility of multilayered architecture with the above stacked upon each other…

EC2-looks like physicalhardware, users can control the entire software stack up the kernel

Clean separation between storageAnd computation tier, automatic scalability and handling of failover

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reasons for later/potential success

o hardwareo illusion of infinite computing resourceso elimination of upfront commitment by userso payment for resources on short-term basis

“past attempts failed because one or two of these features were missing”

Intel Computing Services: - contract, - long-term use than per hour

EC2 --- sells -1.0-GHs x 86 ISA slices for 10 cents per hour

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reasons for later/potential success

o physical infrastructure

“large-scale commodity computer data centers at low-cost location

5 to 7 decrease in cost of”

Electricity Network bandwidth Operations Software Hardware Coupled with statistical multiplexing

o

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reasons for later/potential success

olarge-scale commodity-computer data centerotechnology trends & new applications

mobile interactive applications (real time services)

parallel batch processing (batch-processing, analytic jobs)

business analytic (growth of decision support processing)

computing-extensive desktop applications (MATLAB, Mathematica)

earth-bound services (analytic for long-term financial decisions)

cloud computing: economic logic

o CC has fine-grained economic model--- so trade-off decisions flexibleo CC can track changes in hardware cost and pass them through to the customer

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cloud computing: economic logic

“converting capital cost to economic cost”

(cleverly) rephrased as

“you pay as you go”

o economic sense of CC captured in two fancy terms/concepts

ξ elasticityξ Transference of risk

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cloud computing: economic logic

o elasticity (in acquisition and de-acquisition of resources)

resource addition/removal at fine-grained level so better matching of resources to workload---

users do resource-provisioning for peek-utilization with CC waste of idle resources avoidable---

more effective tackling of over/under provisioning-

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o Visitors receiving poor performance during the peak load permanently lost

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cloud computing: economic logic

o transference of risk (risk of misestimating workload shifted from service operator to cloud vendor)

the cloud vendor may charge a premium (higher use cost per server-hour compared to 3-years purchase cost)

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moving services to clouds: feasibility

pay separately per resource (e.g., CPU-bounded jobs can benefit for paying for CPU separately)

power cooling & physical plant cost (cost double when amortised over building life-time)

operations cost (operations handled by the cloud, lower for managed environments)

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top 10 obstacles to cloud computing

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top 10 obstacles to cloud computing

Availability of service

o multiple clouds --- wouldn’t this add to cost?

o the complex calculations say

DDoS would cost the attacker more thanUntil the attack last for 32 hours but then it would be detected--- (kind of speculative)

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top 10 obstacles to cloud computing

data lock-in

o APIs for CCs proprietary (i.e., not standardized yet)---so difficulty extracting data and programs from one site to run on another---

o solution: standardise APIs for clouds

“race-to-the-bottom” of cloud pricing flattening profit for CC providers-

authors arguments: quality of service, standardization of APIs enabling the use of same software for private as well as public clouds---

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top 10 obstacles to cloud computing

data confidentiality and auditability

o CCs essentially use public networks so more exposed to attacks

o lack of auditability and Accountability Act regulation in CCs

“my sensitive corporation data will never be in the cloud”

authors arguments: same measures e.g., encrypted storage, virtual local area network, and network middleboxes(firewalls, packet filters) as used in in-house IT environment can be employed---

recommendations

o scalability VMs (horizontal scalability of VMs) Application software (needs to rapidly scale-up as well scale-

down, pay for use licensing model)

o infrastructure software (needs to aware of running on VMs, billing built in from the beginning)

o hardware systems To be designed at the scale of container Processors should work with VMs Flash memory added LAN/WAN switches/routers to be improved in bandwidth and cost

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critical review

o overly optimistic/unrealistic view/expectations of/from CLOUD COMPUTING-

o “how CC makes technical sense” aspect not rigorously treated

o Overestimation of economic benefit-probably no real data available to back that up-

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references

1. Armbrust et al., “Above the clouds: a Berkeley view of cloud computing”, 20092. Powell John, “Cloud computing: what it is and what it means for education” 3. Vaquero et al., “A break in the clouds: towards a cloud definition”, CCR online4. http://www.youtube.com/watch?v=IJCxqoh5ep4

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Thanks